Courses Bachelor Display 2020-2021
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Course title | Introduction to Business Analytics | |||||||||||||||||||||||||||||||||||||||
Course code | EBC1042 | |||||||||||||||||||||||||||||||||||||||
ECTS credits | 6,5 | |||||||||||||||||||||||||||||||||||||||
Assessment | Whole/Half Grades | |||||||||||||||||||||||||||||||||||||||
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Level | no level | |||||||||||||||||||||||||||||||||||||||
Coordinator |
Martin Carree For more information: m.carree@maastrichtuniversity.nl |
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Language of instruction | English | |||||||||||||||||||||||||||||||||||||||
Goals |
* Student learn some basics of data-analytic thinking and how it relates to business.
* Students learn how to apply (simple) techniques to datasets/cases. * Students see the interconnection between business and data analytics. * Students can make defendable choices in (simple) data-analytic problems. * Students can investigate a case (firm) in the industry and present their results. * Students are able to communicate their findings during a group presentation. * Students are able to successfully execute a group project plus act as chairman. |
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Description |
PLEASE NOTE THAT THE INFORMATION ABOUT THE TEACHING AND ASSESSMENT METHOD(S) USED IN THIS COURSE IS WITH RESERVATION. THE INFORMATION PROVIDED HERE IS BASED ON THE COURSE SETUP PRIOR TO THE CORONAVIRUS CRISIS. AS A CONSEQUENCE OF THE CRISIS, COURSE COORDINATORS MAY BE FORCED TO CHANGE THE TEACHING AND ASSESSMENT METHODS USED. THE MOST UP-TO-DATE INFORMATION ABOUT THE TEACHING/ASSESSMENT METHOD(S) WILL BE AVAILABLE IN THE COURSE SYLLABUS.
The course serves as an introduction to the bachelor programme. It introduces how business and data science are connected. The course follows a textbook for aspiring data scientists and introduces all kinds of techniques and considerations without going in much detail. Examples of topics include clustering, prediction, visualization, ranking, privacy, etc. There is a matching case used throughout the course to clarify how certain techniques may be used and how firms could benefit from data science solutions. The course indicates the type of business challenges where data analytics can play a fruitful role for businesses to succeed. The course does not involve elaborate programming. Formative assessment: Feedback Summative assessment: Exam, two reports, participation, group presentation and group project |
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Literature |
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Prerequisites |
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Keywords |
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Teaching methods (indicative; course manual is definitive) | ||||||||||||||||||||||||||||||||||||||||
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Evaluation in previous academic year | For the complete evaluation of this course please click "here" | |||||||||||||||||||||||||||||||||||||||
This course belongs to the following programmes / specialisations |
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